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  • Posted: Nov 25, 2024
    Deadline: Not specified
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  • Founded in Australia in 1945, CHEP is a leading provider of pallet and container pooling services for the Aerospace, Automotive, Chemical, Consumer Goods, Fresh Food and Manufacturing industries. CHEP provides equipment pooling which is the shared use of high quality standard pallets and containers by multiple customers. Pooling is a strateg...
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    Team Lead Data Science

    What You’ll Do:

    • Combine math and statistics, specialised programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights.
    • Leads on experimentation with and implementation of new data science techniques on internal/external customer projects.
    • Apply advanced knowledge of Continuous Integration/Continuous Deployment methodologies to deploying and maintaining Machine Learning models reliably and efficiently in Production.
    • Communicate project status, methods, obstacles, and results to wider technical teams and business stakeholders.
    • Managing a small team of data scientists (2) across multiple time zones
    • Lead data science team discussions, providing insight as needed on current approaches and methods

    What will ensure your success in the Role:

    • Degree in Data Science, Computer Science, Engineering, Science, Information Systems and/or equivalent formal training plus work experience
    • Proficient with machine learning models (Supervised; unsupervised; reinforcement) including the productionisation thereof.
    • Proficient with coding in Python, PySpark
    • Proficient with designing and building AI Systems (Decision Intelligence)
    • Extensive experience working with the Databricks Data Intelligence Platform
    • Proficient in researching, developing, synthesizing new algorithms and techniques.
    • Excellent communication skills
    • Extensive experience working in large international corporations.
    • Participated in numerous data science projects.
    • Utilized several data science methodologies.
    • Have worked autonomously and delivered results on schedule.
    • Have presented results to non-data scientist audience.
    • Experience working under different project management frameworks (Waterfall; Agile)
    • Mathematics and Statistics for Data Science

    Preferred Education

    • Bachelors

    Preferred Level of Work Experience

    • 7 - 10 years

    go to method of application »

    Team Lead Data Analysis and Visualisation

    What You’ll Do: 

    • Lead and mentor a team of Insight Analysts, fostering their growth and development.
    • Collaborate with cross-functional teams to understand analytical needs and provide valuable insights.
    • Utilize advanced analytics techniques to extract insights from diverse data sources.
    • Create visually compelling and interactive data visualizations using industry-leading tools.
    • Ensure data accuracy, integrity, and consistency in all analyses and visualizations.
    • Conduct training sessions and workshops to share best practices in data analysis and visualization.
    • Apply complex mathematical and statistical methodologies to support solution delivery and decision-making.
    • Employ creative problem-solving and design thinking to develop innovative solutions.
    • Implement quality control measures to maintain data integrity.
    • Develop compelling, data-driven narratives to inform and influence decision-making.
    • Produce and maintain clear, concise technical documentation.
    • Foster a culture of mentorship and continuous learning within the team.
    • Manage stakeholder relationships and communicate technical capabilities effectively.
    • Align team efforts with the strategic roadmap to maximize business value.
    • Lead thought leadership initiatives and represent the team within and outside the organization.
    • Design, develop, and implement robust business analytics solutions using SQL, DAX, and Python.
    • Build and manage data pipelines, ensuring best practices for data modeling and data quality.
    • Write advanced SQL and DAX queries, and implement solutions to automate processes.
    • Manage and interrogate complex datasets using ThoughtSpot to support business intelligence solutions.

    What will ensure your success in the Role: 

    • Educational Background: Relevant tertiary qualifications in Commerce, Mathematics, Statistics, Computer Science, or related fields.
    • Extensive Experience: Proven track record in data analytics projects, with a background in data visualization and hypothesis testing.

    Technical Proficiency:

    • Expertise in data analysis tools and techniques, including Power BI, Power Apps, Power Automate, SQL, DAX, and Python.
    • Proficiency in workplace tools such as Jira Align, Lucid, Zephyr Scale, and Confluence.
    • Experience in UI design using tools like Figma.
    • Analytical and Problem-Solving Skills: Ability to apply complex methodologies to solve problems and support decision-making.
    • Leadership and Mentorship: Proven experience in leading and developing small teams, with a focus on capability development.
    • Communication Skills: Exceptional verbal and written communication skills to translate complex data into clear, actionable insights.
    • Innovation and Curiosity: A creative and curious mindset, always seeking to improve and innovate in data analysis and visualization.
    • Agile Mindset: Experience working within agile delivery teams and guiding others in adopting agile methodologies.
    • Quality Control: Knowledge of quality management techniques to ensure data accuracy and integrity.
    • Storytelling: Mastery in developing compelling data-driven narratives.
    • Technical Documentation: Ability to produce and maintain impactful technical documentation.
    • Stakeholder Management: Effective communicator and influencer with senior leadership.
    • Strategic Thinking: Ability to align work with the overall business strategy.
    • Thought Leadership: Active in research and development of innovative ideas.

    go to method of application »

    Team Lead Data Engineering

    What You’ll Do:

    • Leadership and Strategy: Oversees the construction and maintenance of highly scalable, robust and fault-tolerant data management and processing systems. Sets the strategic direction for the data engineering team in alignment with organizational goals.
    • Data Models and Architecture: Directs the team in creating and optimizing complex data models that serve as the backbone for data as a product. Sets architectural guidelines to ensure these data models meet all business requirements, reduce system complexity and are aligned with data governance policies.
    • Data as a Product: Ensures that the data generated or processed is of high quality, secure and reliable enough to be considered a stand-alone product. Focuses on data usability and prepares data for analytical and operational uses, thereby creating value for business units and clients.
    • ETL and Data Acquisition: Manages and directs the ETL (Extract, Transform & Load) processes,
    • identifies new opportunities for data acquisition and ensures that data pipelines are secure, efficient and aligned with governance policies.
    • Cost Optimization and Efficiency: Continuously reviews system efficiency and resource utilization to identify areas for cost optimization while maintaining or improving data quality and security.
    • Data Security and Governance: Implements and enforces stringent data governance and security protocols, ensuring compliance with organizational and regulatory standards.
    • Disaster Recovery: Manages the planning and implementation of Disaster Recovery plans and protocols, ensuring rapid data recovery while minimizing loss in the event of a failure.
    • Team Development: Mentors, trains and develops team members to foster a community of data
    • engineering experts who follow best practices, contribute to innovation and uphold data integrity and security.
    • Cross-Functional Collaboration: Works closely with stakeholders, including product managers, business units and other technical teams, to ensure that the data engineering efforts are aligned with broader organizational goals and projects.
    • Audit and Compliance: Regularly conducts audits to ensure data integrity, security and governance and coordinates with compliance teams to address any gaps or vulnerabilities.

    What will ensure your success in the Role:

    • Educational Background: Relevant tertiary qualifications in Computer Science, Statistics, or related technical fields.
    • Extensive Experience: Proven track record in Data Modelling and Data Engineering.

    Technical Proficiency:

    • Expertise in data-related tools and technologies such as SQL, VBA, Python, R, Hadoop, Hive, Spark, Tableau, QlikView, and Power BI.
    • Advanced SQL knowledge and experience with relational databases and query authoring.
    • Familiarity with cloud technologies (AWS S3, RedShift) and integration tools (SSIS, AWS Glue, PySpark).
    • Data modeling skills in SQL Server Analysis Services and Power BI.
    • Analytical Skills: Ability to understand business problems and frame them into a data-driven environment.
    • Data Architecture Knowledge: Understanding of data architecture, engineering methodologies, and best practices.
    • Communication Skills: Excellent written and verbal skills to convey complex technical information to both technical and non-technical stakeholders.
    • Problem-Solving Abilities: Strong analytical skills to tackle complex problems and lead a team in implementing solutions.
    • Collaboration and Teamwork: Ability to work cohesively with colleagues and stakeholders, utilizing tools like JIRA, Lucid, and Zephyr Scale.
    • Leadership and Mentorship: Experience in mentoring and developing team members, and presenting results to senior stakeholders.

    Preferred Education

    • Bachelors

    Preferred Level of Work Experience

    • 7 - 10 years

    Method of Application

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